INTELLIGENT SOFTWARE FOR RADIATION THERAPY PLANNING Besides surgery, radiotherapy is the most effective treatment modality for localized prostate cancer. The success of radiotherapy stems from the exploit of a therapeutic window in tumor response and normal tissue tolerance which maximizes the chance of sterilizing the tumor while sparing the surrounding normal tissue from severe damage. This requires an accurate and individualized radiation dose distribution generated from the examination of the patient?s medical images. Radiation therapy is technically complex and labor intensive. Intensive human supervision and intervention are needed throughout the path of patient care. Artificial intelligence and machine learning technologies are adept at automating workflows and tasks?in this case the development of cancer treatment plans. We believe that this machine learning has incredible potential to address inherent problems in the existing treatment planning workflow. Our approach will mitigate the current issues with treatment planning, integrate seamlessly with day-to-day operations, and will serve as a treatment solution that benefits patients in a way that limits their risk and extends their lives. The goal of this project is to develop a start-to-end prostate cancer treatment planning system. We will work with three expert radiation oncology teams to archive existing patient data for use in training of artificial intelligence algorithms. These algorithms will enable high quality plans to be generated with ease. At the completion of Phase I, we will have a prototype interface that will allow users to create treatment plans and segmentation using artificial intelligence algorithms. Additionally, users will be able to evaluate these plans against other expert plans and against the training data.